免耕栽培模式下油菜菌核病的早期分子检测及预测模型建立  

Molecular detection and forecast model of Sclerotinia rot of rapeseed in no-tillage fields

作　　者：郑露[1] 刘友梅[1] 刘天波[1] 姜道宏[1] 李国庆[1] 黄俊斌[1] 

机构地区：[1]华中农业大学,湖北省作物病害监测与安全控制重点实验室,武汉430070

出　　处：《植物保护学报》2017年第1期103-109,共7页Journal of Plant Protection

基　　金：国家公益性行业(农业)科研专项(201103016);油菜创新技术体系岗位科学家专项(nycytx-00514)

摘　　要：为建立免耕栽培模式下油菜菌核病的早期预测模型,通过巢式PCR法检测湖北省前茬分别为棉花和水稻的2种免耕油菜田花朵带菌率,结合田间调查分析茎秆菌核病发生率与病害主要流行影响因子之间的相关性,并采用主成分分析法建立免耕油菜田花期菌核病的预测模型。结果表明,2009—2012年棉花-油菜田花朵带菌率在同期比水稻-油菜田高,前者花朵带菌率为2.0%~58.2%,后者为0~41.0%。花朵带菌率、子囊盘密度和叶发病率对茎秆发病起主要作用,降雨量和温度作用次之;建立的棉花-油菜和水稻-油菜2种免耕类型田病害预测模型分别为:y=0.261x_1+4.89x_2+0.323x_3+0.32x_4+0.457x_5-9.438,y=0.361x_1+5.824x_2+0.323x_3+0.809x_4+0.333x_5-12.608;且预测值与实际值之间均具有较高的拟合度。表明在花期获得的花朵带菌率、子囊盘密度、叶发病率、降雨量及气温数据,经病害模拟方程可预测当年油菜菌核病发生情况。In order to establish reliable SRR forecast models in no-tillage fields for formulating effective management practices,the percent petal infestations of SRR in cotton-rapeseed and rice-rapeseed fields from Hubei Province were detected by using nested PCR method and the correlations between five epidemic factors and stem disease incidence were analyzed. And SRR forecast model in the two types of no-tillage rapeseed fields were also established by principal component regression. The results showed that the percent petal infestations in cotton-rapeseed fields ranged from 2. 0% to 58. 2% was higher than those in rice-rapeseed fields with 0 to 41. 0% in 2009- 2012. Compared with the factors of precipitation and temperature,more significant correlations with stem disease incidence were found in the percent petal infestation,density of apothecia and foliar disease incidence. Forecast models in cotton-rapeseed and rice-rapeseed fields were established as y = 0. 261x1＋ 4. 89x2＋ 0. 323x3＋ 0. 32x4＋ 0. 457x5- 9. 438 and y = 0. 361x1＋ 5. 824x2＋ 0. 323x3＋ 0. 809x4＋ 0. 333x5- 12. 608,respectively. And the predicted values were close to the actual values in these two models. Therefore,the models based on measuring the percent petal infestation, density of apothecia, foliar disease incidence, mean precipitation and temperature during bloom stage could be used in SRR monitoring and prediction.

关 键 词：免耕田 油菜 菌核病 分子检测 预测模型 

分 类 号：S435.654[农业科学—农业昆虫与害虫防治]